Compare Palantir Foundry and Vertex AI 
Featured Products
At a Glance
Market Segments
Small-Business (35.7% of reviews)
Small-Business (42.0% of reviews)
Entry-Level Pricing
No pricing available
Pay As You Go Per Month
Palantir Foundry
Star Rating
(14)4.1 out of 5
Market Segments
Small-Business (35.7% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Palantir FoundryVertex AI
Star Rating
(651)4.3 out of 5
Market Segments
Small-Business (42.0% of reviews)
Pros & Cons
Entry-Level Pricing
Pay As You Go Per Month
Learn more about Vertex AISummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Vertex AI excels in managing complex machine learning workflows, with users highlighting its ability to centralize the entire ML lifecycle—from data preparation to deployment—making it a favorite for those looking for a comprehensive solution.
- Users say that Palantir Foundry provides a good experience with its ease of use and integration capabilities, allowing teams to incorporate AI workflows into their existing tech stack seamlessly, which is particularly beneficial for organizations looking to enhance their data ecosystem.
- Reviewers mention that Vertex AI's integration with Google Cloud is a significant advantage, simplifying the management of machine learning projects and reducing the effort required to build, train, and deploy models, which is a key factor for many users.
- According to verified reviews, while Palantir Foundry has received praise for its support and ease of implementation, some users feel it doesn't quite match the overall satisfaction and feature richness that Vertex AI offers, particularly in terms of handling the full ML lifecycle.
- Users highlight that Vertex AI's high ratings in quality of support and product direction indicate a strong commitment to user needs, with many appreciating the responsive assistance and ongoing improvements that enhance their experience.
- G2 reviewers note that while both platforms cater to small businesses, Vertex AI's larger volume of recent reviews and higher overall satisfaction scores suggest it may be a more reliable choice for those seeking a robust data science and machine learning platform.
Pricing
Entry-Level Pricing
Palantir Foundry
No pricing availableVertex AI
Try Vertex AI Free
Pay As You Go
Per Month
New customers get $300 in free credits to spend on Vertex AI.
- A unified UI for the entire ML workflow
- Pre-trained APIs for vision, video, natural language, and more
- End-to-end integration for data and AI
Free Trial
Palantir Foundry
No trial information availableVertex AI
No trial information availableRatings
Meets Requirements
7.9
11
8.6
389
Ease of Use
7.6
11
8.2
400
Ease of Setup
Not enough data
8.1
322
Ease of Admin
Not enough data
7.9
149
Quality of Support
7.7
11
8.1
364
Has the product been a good partner in doing business?
Not enough data
8.3
143
Product Direction (% positive)
6.4
13
9.2
383
Features by Category
Data Source Access
7.6
7
Not enough data
6.7
7
Not enough data
6.4
6
Not enough data
Data Interaction
7.2
6
Not enough data
6.9
6
Not enough data
7.4
7
Not enough data
6.9
6
Not enough data
6.9
6
Not enough data
7.2
6
Not enough data
6.9
6
Not enough data
7.9
7
Not enough data
Data Exporting
6.9
6
Not enough data
7.5
6
Not enough data
7.6
7
Not enough data
Generative AI
Not enough data
Not enough data
Deployment
Not enough data
8.4
76
Not enough data
8.1
78
Not enough data
8.3
76
Not enough data
8.4
76
Not enough data
8.8
75
Deployment
Not enough data
8.5
75
Not enough data
8.3
73
Not enough data
8.4
72
Not enough data
8.6
74
Not enough data
8.7
71
Management
Not enough data
8.2
71
Not enough data
8.5
73
Not enough data
8.0
71
Not enough data
8.1
70
Operations
Not enough data
8.2
70
Not enough data
8.5
71
Not enough data
8.3
71
Management
Not enough data
8.1
69
Not enough data
8.4
72
Not enough data
8.3
70
Generative AI
Not enough data
8.4
37
Not enough data
8.6
37
System
Not enough data
8.2
173
Model Development
Not enough data
8.5
208
Not enough data
7.9
181
Not enough data
8.4
206
Not enough data
8.5
209
Model Development
Not enough data
8.2
167
Machine/Deep Learning Services
Not enough data
8.3
203
Not enough data
8.5
202
Not enough data
8.2
200
Not enough data
8.3
181
Machine/Deep Learning Services
Not enough data
8.5
167
Not enough data
8.5
166
Deployment
Not enough data
8.3
213
7.3
5
8.3
203
Not enough data
8.6
207
Generative AI
Not enough data
8.3
110
Not enough data
8.3
106
Not enough data
8.1
105
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
38
Not enough data
7.8
37
Not enough data
7.7
38
Not enough data
7.9
35
Not enough data
8.5
37
Not enough data
7.5
36
Not enough data
7.7
36
Data Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Analytics
Not enough data
Not enough data
Security
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Agentic AI - Data Fabric
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Development
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Integration Options
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Deployment
Not enough data
Not enough data
Not enough data
Not enough data
Management
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Functionality
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Security
Not enough data
Not enough data
Not enough data
Not enough data
Scalability and Performance - Generative AI Infrastructure
Not enough data
9.0
31
Not enough data
8.7
32
Not enough data
8.6
31
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.0
34
Not enough data
7.7
31
Not enough data
8.1
30
Integration and Extensibility - Generative AI Infrastructure
Not enough data
8.5
30
Not enough data
8.3
32
Not enough data
8.5
31
Security and Compliance - Generative AI Infrastructure
Not enough data
8.7
30
Not enough data
8.3
32
Not enough data
8.9
30
Usability and Support - Generative AI Infrastructure
Not enough data
8.2
31
Not enough data
8.5
31
Integration - Machine Learning
Not enough data
8.5
68
Learning - Machine Learning
Not enough data
8.5
66
Not enough data
8.3
65
Not enough data
8.8
66
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
9.0
26
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
24
Not enough data
9.0
24
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.3
25
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
24
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
23
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
23
Not enough data
8.7
22
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
23
Not enough data
8.9
22
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
21
Not enough data
9.1
22
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
9.0
23
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
22
Customization - AI Agent Builders
Not enough data
8.6
28
Not enough data
7.6
27
Not enough data
8.3
26
Functionality - AI Agent Builders
Not enough data
8.1
27
Not enough data
7.3
27
Not enough data
8.2
26
Not enough data
7.2
27
Data and Analytics - AI Agent Builders
Not enough data
7.8
26
Not enough data
7.9
27
Not enough data
8.1
28
Integration - AI Agent Builders
Not enough data
8.8
28
Not enough data
8.2
30
Not enough data
8.1
28
Not enough data
7.5
27
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Statistical Tool
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Analysis
Not enough data
Not enough data
Not enough data
Not enough data
Decision Making
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Generative AI
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Palantir Foundry and Vertex AI are categorized as Data Science and Machine Learning Platforms
Unique Categories
Palantir Foundry is categorized as Data Preparation, Predictive Analytics, Master Data Management (MDM), Data Fabric, Big Data Integration Platforms, and iPaaS
Vertex AI is categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, MLOps Platforms, Machine Learning, AI Agent Builders, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
Palantir Foundry
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Vertex AI
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
21.4%
Computer Software
21.4%
Pharmaceuticals
14.3%
Information Services
7.1%
Government Administration
7.1%
Other
28.6%
Computer Software
17.9%
Information Technology and Services
14.3%
Financial Services
6.8%
Retail
3.6%
Hospital & Health Care
3.3%
Other
54.1%
Alternatives
Discussions
Palantir Foundry has no discussions with answers
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